When should I use subagents in my design?

Subagents should be used for isolated child tasks where extensive exploration or verbose output might pollute the main agent's context window.

What is the core philosophy of the AI Agent Builder skill?

The core philosophy is that the model IS the agent; the code's primary role is to provide a loop that offers the model capabilities, knowledge, and context to act.

How many capabilities should I give a new AI agent?

It is best to start with 3-5 atomic capabilities. You should only add more once usage shows that the agent consistently fails because a specific tool is missing.

What are the common anti-patterns in agent building?

Common mistakes include over-engineering with rigid workflows, front-loading too much knowledge into the context, and providing too many capabilities which can confuse the model.

Does this skill work for building specialized business agents?

Yes, the agentic pattern provided is universal and can be applied to CRM management, research, customer service, or any domain by changing the capabilities and knowledge.

AI Agent Builder

Name: AI Agent Builder
Author: shareAI-lab

byshareAI-lab

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15,998

データサイエンスとML

Designs and builds autonomous AI agents by providing architectural frameworks for capabilities, knowledge management, and agentic loops.

概要

AI Agent Builder is a specialized Claude Code skill designed to streamline the creation of autonomous AI systems across business, research, and operational domains. By adhering to a 'model-first' philosophy, it guides users in constructing lean agentic loops that leverage the inherent reasoning of LLMs rather than over-engineered code. This skill provides the implementation patterns for atomic capabilities, dynamic knowledge injection, and context isolation, making it ideal for developers building everything from simple assistants to complex multi-step orchestrators.

主な機能

Agentic loop architecture and implementation
Progressive complexity scaling from basic to planning
15,998 GitHub stars
Atomic capability (tool use) design principles
Dynamic domain-specific knowledge injection
Subagent patterns for context isolation

ユースケース

Designing business automation agents for CRM management and workflow orchestration
Creating an operations agent for system monitoring, ticket triage, and escalation
Building a research assistant that automates database queries and document analysis

概要

主な機能

Agentic loop architecture and implementation
Progressive complexity scaling from basic to planning
15,998 GitHub stars
Atomic capability (tool use) design principles
Dynamic domain-specific knowledge injection
Subagent patterns for context isolation

ユースケース

Designing business automation agents for CRM management and workflow orchestration
Creating an operations agent for system monitoring, ticket triage, and escalation
Building a research assistant that automates database queries and document analysis